182 related articles for article (PubMed ID: 25933428)
1. Predicting human genetic interactions from cancer genome evolution.
Lu X; Megchelenbrink W; Notebaart RA; Huynen MA
PLoS One; 2015; 10(5):e0125795. PubMed ID: 25933428
[TBL] [Abstract][Full Text] [Related]
2. Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer.
Srihari S; Singla J; Wong L; Ragan MA
Biol Direct; 2015 Oct; 10():57. PubMed ID: 26427375
[TBL] [Abstract][Full Text] [Related]
3. Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization.
Huang J; Wu M; Lu F; Ou-Yang L; Zhu Z
BMC Bioinformatics; 2019 Dec; 20(Suppl 19):657. PubMed ID: 31870274
[TBL] [Abstract][Full Text] [Related]
4. Link synthetic lethality to drug sensitivity of cancer cells.
Wang R; Han Y; Zhao Z; Yang F; Chen T; Zhou W; Wang X; Qi L; Zhao W; Guo Z; Gu Y
Brief Bioinform; 2019 Jul; 20(4):1295-1307. PubMed ID: 29300844
[TBL] [Abstract][Full Text] [Related]
5. Identifying collateral and synthetic lethal vulnerabilities within the DNA-damage response.
Pinoli P; Srihari S; Wong L; Ceri S
BMC Bioinformatics; 2021 May; 22(1):250. PubMed ID: 33992077
[TBL] [Abstract][Full Text] [Related]
6. An integrative multi-network and multi-classifier approach to predict genetic interactions.
Pandey G; Zhang B; Chang AN; Myers CL; Zhu J; Kumar V; Schadt EE
PLoS Comput Biol; 2010 Sep; 6(9):. PubMed ID: 20838583
[TBL] [Abstract][Full Text] [Related]
7. Ranking novel cancer driving synthetic lethal gene pairs using TCGA data.
Ye H; Zhang X; Chen Y; Liu Q; Wei J
Oncotarget; 2016 Aug; 7(34):55352-55367. PubMed ID: 27438146
[TBL] [Abstract][Full Text] [Related]
8. Genome-wide prediction of functional gene-gene interactions inferred from patterns of genetic differentiation in mice and men.
Bochdanovits Z; Sondervan D; Perillous S; van Beijsterveldt T; Boomsma D; Heutink P
PLoS One; 2008 Feb; 3(2):e1593. PubMed ID: 18270580
[TBL] [Abstract][Full Text] [Related]
9. Overcoming selection bias in synthetic lethality prediction.
Seale C; Tepeli Y; Gonçalves JP
Bioinformatics; 2022 Sep; 38(18):4360-4368. PubMed ID: 35876858
[TBL] [Abstract][Full Text] [Related]
10. SLGNN: synthetic lethality prediction in human cancers based on factor-aware knowledge graph neural network.
Zhu Y; Zhou Y; Liu Y; Wang X; Li J
Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36645245
[TBL] [Abstract][Full Text] [Related]
11. Genetic and epigenetic heterogeneity in cancer: a genome-centric perspective.
Heng HH; Bremer SW; Stevens JB; Ye KJ; Liu G; Ye CJ
J Cell Physiol; 2009 Sep; 220(3):538-47. PubMed ID: 19441078
[TBL] [Abstract][Full Text] [Related]
12. SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets.
Guo J; Liu H; Zheng J
Nucleic Acids Res; 2016 Jan; 44(D1):D1011-7. PubMed ID: 26516187
[TBL] [Abstract][Full Text] [Related]
13. Identifying features of genome evolution to exploit cancer vulnerabilities.
Dandage R; Landry CR
Cell Syst; 2021 Dec; 12(12):1127-1130. PubMed ID: 34914903
[TBL] [Abstract][Full Text] [Related]
14. Using graph-based model to identify cell specific synthetic lethal effects.
Pu M; Cheng K; Li X; Xin Y; Wei L; Jin S; Zheng W; Peng G; Tang Q; Zhou J; Zhang Y
Comput Struct Biotechnol J; 2023; 21():5099-5110. PubMed ID: 37920819
[TBL] [Abstract][Full Text] [Related]
15. In silico prediction of synthetic lethality by meta-analysis of genetic interactions, functions, and pathways in yeast and human cancer.
Wu M; Li X; Zhang F; Li X; Kwoh CK; Zheng J
Cancer Inform; 2014; 13(Suppl 3):71-80. PubMed ID: 25452682
[TBL] [Abstract][Full Text] [Related]
16. Building high-resolution synthetic lethal networks: a 'Google map' of the cancer cell.
Paul JM; Templeton SD; Baharani A; Freywald A; Vizeacoumar FJ
Trends Mol Med; 2014 Dec; 20(12):704-15. PubMed ID: 25446836
[TBL] [Abstract][Full Text] [Related]
17. Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality.
Jerby-Arnon L; Pfetzer N; Waldman YY; McGarry L; James D; Shanks E; Seashore-Ludlow B; Weinstock A; Geiger T; Clemons PA; Gottlieb E; Ruppin E
Cell; 2014 Aug; 158(5):1199-1209. PubMed ID: 25171417
[TBL] [Abstract][Full Text] [Related]
18. SL-scan identifies synthetic lethal interactions in cancer using metabolic networks.
Zangene E; Marashi SA; Montazeri H
Sci Rep; 2023 Sep; 13(1):15763. PubMed ID: 37737478
[TBL] [Abstract][Full Text] [Related]
19. Predicting essential genes and synthetic lethality via influence propagation in signaling pathways of cancer cell fates.
Zhang F; Wu M; Li XJ; Li XL; Kwoh CK; Zheng J
J Bioinform Comput Biol; 2015 Jun; 13(3):1541002. PubMed ID: 25669329
[TBL] [Abstract][Full Text] [Related]
20. Understanding genomic alterations in cancer genomes using an integrative network approach.
Wang E
Cancer Lett; 2013 Nov; 340(2):261-9. PubMed ID: 23266571
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
